🚀 Our latest benchmark shows hyperparameter tuning with Optuna hits 0.9617 validation accuracy in just 64.59 seconds! Using Bayesian optimization and the Tree‑structured Parzen Estimator, we ran 100 trials to squeeze out every percent. Dive into the details of the experiment and see how you can apply these tricks to your own models. #HyperparameterTuning #Optuna #BayesianOptimization #ModelOptimization

🔗 https://aidailypost.com/news/hyperparameter-tuning-reaches-09617-accuracy-6459-seconds

Pipeline release! nf-core/drugresponseeval v1.1.0 - Drugresponseeval 1.1.0 - Humongous Zapdos!

Please see the changelog: https://github.com/nf-core/drugresponseeval/releases/tag/1.1.0

#celllines #crossvalidation #deeplearning #drugresponse #drugresponseprediction #drugs #fairprinciples #generalization #hyperparametertuning #machinelearning #randomizationtests #robustnessassessment #training #nfcore #openscience #nextflow #bioinformatics

Pipeline release! nf-core/drugresponseeval v1.0.0 - 1.0.0!

Please see the changelog: https://github.com/nf-core/drugresponseeval/releases/tag/1.0.0

#celllines #crossvalidation #deeplearning #drugresponse #drugresponseprediction #drugs #fairprinciples #generalization #hyperparametertuning #machinelearning #randomizationtests #robustnessassessment #training #nfcore #openscience #nextflow #bioinformatics

Discover how #HyperparameterTuning with #GridSearchCV can revolutionize your #TeslaStock predictions! This guide walks you through optimizing #MachineLearning models for more accurate forecasts. Boost your trading strategy with data-driven insights!

https://teguhteja.id/hyperparameter-tuning-for-tesla-stock-prediction-with-gridsearchcv/

📚 Dive into an enlightening exploration of hyperparameter tuning in machine learning! Learn about optimization techniques, challenges, and best practices to boost your model's performance. 🚀 Check it out: https://ak-codes.com/hyperparameter-tuning/ #MachineLearning #HyperparameterTuning

Dive into this fascinating example of transfer learning and hyperparameter tuning for image classification tasks! 📸🎓 #MachineLearning #TransferLearning #HyperparameterTuning https://ak-codes.com/transfer-learning-example/

https://github.com/google-research/tuning_playbook

New initiative from Google research with the goal of formalizing the process of hyperparameter tuning in DL. Seems to be trending pretty hard (about 1.5k github stars in the last 8 hours alone).
I've been playing around with keras-tuner recently and have definitely felt the need for something similar to this to refer to for numerous decisions. Interesting to see where this goes.

#Google #deeplearning #dl #hyperparametertuning